Measurement of Nitrate-Nitrogen Concentration in Soil based on Absorption Spectroscopy

ABSTRACT

The nitrate-nitrogen concentration in soil is estimated based on the nitrate-nitrogen 200 nm absorption peak. In one embodiment, a device measures the attenuation spectrum of a soil-extractant mixture over a wavelength range that includes wavelengths in the vicinity of the 200 nm absorption peak (the spectral operating range) and then determines the nitrate-nitrogen concentration based on the attenuation spectrum.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/215,696, filed May 7, 2009, which is incorporated by reference in itsentirety.

BACKGROUND

1. Field of Art

The present invention generally relates to measurement ofnitrate-nitrogen concentrations in soil.

2. Description of the Related Art

Nutrient levels in soil have significant spatial and temporalvariations. Accordingly, there has been significant effort placed intodevelopment of local nutrient management schemes, often referred to as“precision agriculture,” addressing nutrient level variation. Localnutrient management increases agricultural efficiency while reducing itsenvironmental impact by allowing growers to locally apply nutrientswhere needed. Increases in nutrient costs and a growing awareness of theenvironmental consequences of current agriculture practices have madeimprovements in agricultural efficiency and environmental impactincreasingly important.

Nitrate-nitrogen is one of most important nutrients for a variety ofcrops, but it is particularly mobile in the soil, making it subject tolarge spatial variations. The conventional approach to nitrate-nitrogenmeasurement is based on laboratory-based soil measurements. Soil samplesare typically mailed to the labs, where the samples are unpacked,sorted, dried, ground, and then measured. This process is fairlyexpensive and can take up to two weeks before results are available.This can be a significant drawback.

As an example, in-season nitrogen management in corn-growing regions isoften difficult because of the slow turnaround time of laboratory-basedsoil testing. Extending the time when corn growers are able to measuresoil nitrogen levels would allow corn growers to test fields beforetheir last application of fertilizer. This would enable corn growers totest fields later in the growing season and implement better nitrogenmanagement practices. Further, allowing growers to promptly retestfields, such as retesting after a rain, would allow growers to adoptmore efficient nitrogen management practices. Additionally,laboratory-based soil measurement costs scale directly with the numberof samples, making it prohibitively expensive to sample at high griddensities.

As a result, there has been interest in developing faster, simplerand/or less expensive soil measurement techniques to expand the benefitsof precision agriculture. Technologies used have ranged frommid-infrared (mid-IR) spectroscopy to ion-selective electrodes. However,each of these methods has suffered from some combination of expense, lowaccuracy, stringent calibration requirements or difficulty of use.

One approach is based on canopy sensors and satellite imagery that canmeasure NDVI (normalized difference vegetative index), which isessentially a color measurement that can be used to infer nitrogenneeds. These methods are typically fast and operate on a relatively lowcost/acre. Unfortunately, there are numerous interferences to NDVImeasurements, as many factors can affect crop color, such as water needsand disease. Thus, it appears to suffer from low accuracy. Additionally,this method requires a dense crop canopy to be useful, which puts atight operational limit on its use. It can only be used fairly late inthe season.

There have also been several recent efforts to perform fast “on-the-go”measurements of soil nitrate-nitrogen using ion-selective electrodes.However, the fragility of the ion-selective membrane has causedsignificant problems with the robustness and reproducibility of soilmeasurements. Ion-selective systems also require frequent calibration,making them unappealing for routine field use.

Nitrate “strip tests,” commonly available from scientific supply storesor from manufacturers, have also been used. However, nitrate strip teststypically suffer from poor accuracy compared to standardlaboratory-based tests and require extensive sample preparation,including consumable reagents. For example, the standard preparationtime for nitrate strip tests typically approaches 30 minutes, includesnumerous preparation steps and requires precise timing of the reactionsteps.

In another recent approach, optical absorption has been used for in-situmonitoring of soil nitrate content. However, this approach was based ona filtering method, in which an optical probe was encapsulated inside aporous stainless steel casing. As a result, the method suffered fromvery slow measurement times (in the tens of hours). In addition, thisapproach was focused on measuring the nitrate absorption peak at 300 nm.However, the peak at 300 nm has a relatively weak absorption crosssection, and so presents difficulties when measuring nitrateconcentration values typically found in agricultural soils. For example,experimental results based on the 300 nm peak typically do notdemonstrate sensitivity below 100 ppm nitrate-nitrogen concentration,whereas agronomically relevant levels of soil nitrate-nitrogenconcentration are in the 0-50 ppm range.

Accordingly, a rapid and economical soil nitrate-nitrogen measurementsystem could significantly increase the efficiency of agriculturalnitrate use.

SUMMARY

The present invention overcomes the limitations of the prior art byestimating the nitrate-nitrogen concentration in soil based on thenitrate-nitrogen 200 nm absorption peak. In one embodiment, a devicemeasures the attenuation spectrum (which could include effects due toscattering in addition to absorption) of a soil-extractant mixture overa wavelength range that includes wavelengths in the vicinity of the 200nm absorption peak and then determines the nitrate-nitrogenconcentration based on the attenuation spectrum. The wavelength rangewill be referred to as the spectral operating range.

In one implementation, such a device includes a light source, adetector, a sample chamber and a processor. The light source generateslight that spans the spectral operating range, including sufficientamounts of light in the vicinity of 200 nm (but not necessarilyincluding 200 nm). The sample chamber holds a soil-extractant mixture(e.g., a water-soil mixture). The light propagates from the lightsource, through the soil-extractant mixture in the sample chamber, tothe detector. Due to the high absorption at 200 nm, the path lengththrough the soil-extractant mixture is short, for example 2 mm or lessin many cases. The detector (e.g., a spectrometer) generates a signalthat indicates the light received by the detector at differentwavelengths across the spectral operating range (the soil spectralsignal). The processor uses the soil spectral signal to calculate anattenuation spectrum for the water-soil mixture, and then estimates thenitrate-nitrogen concentration based on the attenuation spectrum.Various approaches are based on analyzing the attenuation spectrum inorder to estimate the strength of the nitrate-nitrogen absorption peakat 200 nm.

In one approach, the processor determines the attenuation spectrum basedon the soil spectral signal, a reference spectral signal and a darkspectral signal. The reference spectral signal is generated when thesample chamber contains just the extractant without soil, and the darkspectral signal is generated without light from the light sourceincident on the detector. These three signals can be generated atdifferent times and in different manners. For example, some or all ofthe signals can be generated at different times using the sameequipment. The reference spectral signal and dark spectral signal couldbe generated as part of a calibration process. A separate referencechamber could be used to generate the reference spectral signal inparallel with the soil spectral signal. Other variations will beapparent.

The spectral operating range is selected to adequately estimate the 200nm absorption peak, which has a 20 nm full width half max. It usuallywill also extend into longer wavelengths (e.g., the visible, near IRand/or mid IR) in order to provide enough data to sufficiently accountfor contributions from other sources (e.g., nitrite-nitrogen, soilscattering, humic acids, organic matter/carbon, inorganic salts, etc.).The light source is selected to provide sufficient power at thewavelengths of interest. The light source preferably has sufficientpower at the deep UV range (around 200 nm) relative to the longerwavelengths so that the longer wavelengths do not dominate the detectorresponse.

Once the attenuation spectrum is calculated, the nitrate-nitrogenconcentration can be determined using a number of different approaches.The attenuation spectrum around 200 nm includes the nitrate-nitrogenpeak but also includes contributions from other sources. These othersoil interferences are taken into account when estimating thenitrate-nitrogen concentration. Some approaches are based on physicalmodels of the contributions from different sources. For example, themeasured attenuation spectrum can be modeled as the sum of contributionsfrom different sources, where the spectral shape of each contribution isknown or modeled. Regression can be used to then determine the relativeweights of each contribution, which in turn can be used to estimate theconcentration of each source.

In another approach, the contributions from the other soil interferencesmay be well known or separately determined. These can then be subtractedfrom the attenuation spectrum, leaving an estimate of the absorptionpeak at 200 nm. A Gaussian function can be fitted to this residual peakto estimate the nitrate-nitrogen concentration.

Other approaches are more empirical, for example based on training usingactual samples with known nitrate-nitrogen concentrations. Partial leastsquares regression is one possible empirical approach. Partial leastsquares regression is a multivariate statistical analysis technique thatcan extract the correlation of the nitrate-nitrogen absorption peak at200 nm to the nitrate-nitrogen concentration value independent of thebackground interferences.

In some cases, the processor can also take advantage of time dynamics toestimate concentrations before the soil-extractant mixture actuallyreaches the steady state concentration. The extraction of soilcomponents has some time constant. It may take some time before thesoil-extractant mixture is homogenous with respect to a particular soilcomponent. The concentration can be measured at different times duringthe extraction process. The data points can then be extrapolated toyield the steady state concentration before the soil-extractant mixturehas reached that steady state, thus saving time in the overall process.

The speed with which nitrate is released from soil depends in part onthe type of soil and how quickly the soil is broken up. With a morevigorous mechanism for breaking up the soil, nitrate-nitrogenconcentration should be estimated in 60 seconds or less, essentiallyreal-time.

The approaches described above can also be combined with othertechniques. For example, filtering or centrifuging can be used toprocess the soil sample. Information obtained from other sources, suchas soil type, moisture, conductivity, temperature, ambient humidity andpH, can also be used in the estimate of the nitrate-nitrogenconcentration.

The features and advantages described in the specification are not allinclusive and, in particular, many additional features and advantageswill be apparent to one of ordinary skill in the art in view of thedrawings, specification, and claims. Moreover, it should be noted thatthe language used in the specification has been principally selected forreadability and instructional purposes, and may not have been selectedto delineate or circumscribe the inventive subject matter.

BRIEF DESCRIPTION OF DRAWINGS

The disclosed embodiments have other advantages and features which willbe more readily apparent from the following detailed description and theappended claims, when taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 is a block diagram of a soil analysis device according to theinvention.

FIG. 2 is a flow diagram illustrating operation of the device in FIG. 1.

FIG. 3 is a diagram of another soil analysis device according to theinvention.

FIGS. 4A and 4B are graphs of an attenuation spectrum, identifyingcontributions from different sources.

FIG. 5 is a graph illustrating curve fitting to an attenuation spectrum.

FIG. 6 is a graph summarizing experiments testing the accuracy of theinvention.

FIG. 7 is a graph of nutrient concentration as a function of time.

DETAILED DESCRIPTION

The figures and the following description relate to preferredembodiments of the present invention by way of illustration only. Itshould be noted that from the following discussion, alternativeembodiments of the structures and methods disclosed herein will bereadily recognized as viable alternatives that may be employed withoutdeparting from the principles of the claimed invention.

FIG. 1 is a block diagram of a soil analysis device according to theinvention. The device includes a light source 110, a sample chamber 120,a detector 130 and a processor 140. The sample chamber 120 is configuredto contain a soil-extractant mixture. It is optically positioned betweenthe light source 110 and detector 130, so that light 150 from source 110propagates through the soil-extractant mixture and to the detector 130.The processor 140 is coupled to the detector 130.

The device measures the nitrate-nitrogen concentration in soil using thenitrate-nitrogen absorption peak at 200 nm. In this example, the devicedoes this by considering the attenuation spectrum of a soil-extractantmixture across a broad wavelength range (which will be referred to asthe spectral operating range) that includes wavelengths in the vicinityof the 200 nm absorption peak.

FIG. 2 is a flow diagram illustrating the operation of this device. Asoil-extractant mixture is provided 210 in the sample chamber 120. Thelight source 110 generates 220 light that spans the spectral operatingrange and this light illuminates the sample chamber 120. The lightpropagates 230 through the soil-extractant mixture and is attenuated bydifferent amounts at different wavelengths. The exiting light isincident on the detector 130 (typically a spectrometer), which detects240 the amount of light at different wavelengths. The resulting signalgenerated 250 by the detector 130 will be referred to as the soilspectral signal, to indicate that it is a spectrum across manywavelengths that accounts for attenuation by soil. The detector 130 issensitive across the spectral operating range. The processor 140estimates 260 the attenuation spectrum of the soil-extractant mixturebased on the soil spectral signal. The attenuation spectrum iscalculated over the spectral operating range. The processor 140 thenestimates 270 the nitrate-nitrogen concentration based on theattenuation spectrum.

In more detail, the spectral operating range typically includes both thedeep UV and the visible. Since this device is based on the absorptionpeak at 200 nm, the spectral operating range includes wavelengths in thevicinity of this peak in order to estimate the strength of theabsorption. For example, the spectral operating range could include (butis not limited to) at least 10 nm to either side of 200 nm (i.e.,190-210 nm or 20 nm full width half max), preferably 20 nm (180-220 nm)or more preferably 30 nm (170-230 nm). The spectral operating range isnot required to include 200 nm. The 200 nm absorption peak has a 20 nmwidth, so wavelengths to either side of the peak can be sufficient toestimate the peak. For example, the spectral operating range may includewavelengths that are only to one side of the peak: 205 nm and longer,210 nm and longer, or 215 nm and longer. Even ranges as far removed as230 nm and longer can possibly yield good results depending on thesituation. Estimating the 200 nm absorption peak typically determinesthe lower end of the spectral operating range. More wavelength samplesaround this peak generally will lead to better results. However, theabsorption peak has a 20 nm full width half max, so extending thespectral operating range down to 160-170 nm represents a range of 3-4widths below the peak.

On the high end, the spectral operating range should be sufficient toaccount for spectral contributions other than nitrate-nitrogenabsorption. Thus, the spectral operating range typically extends intoand possibly beyond the visible. Typical spectral operating ranges mayextend to somewhere in the 500-1100 nm range on the high end, althoughwavelengths outside this range are also possible.

Given the low end and high end considerations, typical spectraloperating ranges include 150-500 nm, 150-850 nm, 150-1100 nm, 170-1100nm, 180-1100 nm, 190-500 nm and 190-850 nm. The spectral operating rangedoes not have to be continuous over a wavelength range. For example, ifthe light source 110 includes multiple devices, the spectral operatingrange might be 180-220 and 400-800 nm. It might also include discretesources, sources with tunable emission wavelengths, or narrow wavelengthlines.

FIG. 3 is a diagram of another soil analysis device according to theinvention. In FIG. 3, the light source, detector and processor are notshown. The sample chamber 320 is defined by two quartz optical windows,which transmit well at 200 nm. The incoming light is delivered by fiber312 and the exiting light is collected by fiber 332. The soil-extractantmixture is created in mixing chamber 370 which is connected to thesample chamber 320.

In one specific design, the light source is a Heraeus UV-Vis FiberLightmodel DTM 6/50S. This light source has two separately controllablebulbs. One bulb is stronger in the UV compared to the other bulb.Separate controls allows the user or manufacturer to adjust the UVcontent of the illuminating light relative to the visible content. Theoptical fibers are standard silica fibers. The detector is a StellarnetEPP2000C spectrometer, with a wavelength range of 190-850 nm. Analternate detector is the Ocean Optics Maya2000Pro spectrometer, with awavelength range from 175-1100 nm. The spectrometer wavelength range isnarrower than the light source, so the spectrometer determines thespectral operating range which is 190-850 nm or 175-1100 nm in theseexamples.

The extractant in this example is water. The water-soil mixture is about1-1.5% soil by weight, for example 5-7.5 g of soil mixed with 460 mL ofwater. More soil can be used, so long as enough light is transmitted tothe detector. For example, higher percentages (5%) of soil can be usedwith soils that are less optically absorbing. Less soil can also beused, so long as the nitrate-nitrogen signal is sufficiently strong.Other extractants include, but are not limited to, potassium chloride;ammonium fluoride and hydrochloric acid (Bray method); sodiumbicarbonate (Olsen method); or ammonium-nitrate, acedic acid, ammoniumfluoride, and EDTA (Mehlic method).

The soil is mixed with the water by a motorized stirrer. Othermechanisms such as heating or ultrasound can also be used to increasethe speed of extraction of the relevant soil nutrients into thewater-soil mixture. Filtering, centrifuging, mechanical separation orother approaches may be used to additionally prepare the mixture. Thisparticular design does not use filtering or centifuging in order toavoid the added complexity and longer processing time.

The water-soil mixture enters the sample chamber 320 and attenuates thelight passing through it. Due to the high absorption, the path of thelight through the water-soil mixture preferably is short, typically 1 cmor less, generally less than 2 mm.

The spectrometer detects the remaining light after attenuation by thewater-soil mixture. This signal is referred to as the soil spectralsignal, I_(soil). This spectrometer samples the spectral operating rangeat 1 nm wavelength increments, or roughly 650 samples over the entirewavelength range. Other wavelength sampling can be used. For example,the sampling may be finer around the 200 nm absorption peak (or anyother areas where a narrower spectral feature is expected) and coarserin regions where only broad spectral features are expected. The nitrateabsorption peak has a Gaussian width of ˜20 nm, which could bereasonably sampled with 5 nm resolution in most cases.

The processor estimates the attenuation spectrum based on the soilspectral signal I_(soil). In this design, it also uses two additionalsignals: a reference spectral signal I_(ref) and a dark spectral signalI_(dark). The reference spectral signal I_(ref) is the response when thesample chamber is filled with water but no soil. The dark spectralsignal I_(dark) is the response when no light is incident on thedetector. For example, the light source can be turned off or blocked.The attenuation spectrum is then calculated as

α(λ)=−log₁₀ {[I _(soil)(λ)−I _(dark)(λ)]/[I _(ref)(λ)−I_(dark)(λ)]}  (1)

Note that this approach is normalized with respect to spectralvariations in source power.

The measurements I_(soil), I_(ref) and I_(dark) can be taken atdifferent times and in different ways with respect to each other. Forexample, the measurements can be time multiplexed. At one time, thelight source is turned off or blocked for I_(dark). At another time, thelight source is turned on and the sample chamber filled with water forI_(ref). At a third time, the sample chamber is filled with thewater-soil mixture for I_(soil). The different measurements can be madewith different frequencies. For example, I_(ref) and I_(dark) do nothave to be measured for every sample measurement of I_(soil). In oneapproach, I_(ref) and I_(dark) are measured periodically (e.g., once perhour, or once per day, or once per some calibration period), or as partof a calibration procedure.

In an alternate approach, the measurements I_(soil), I_(ref) andI_(dark) can be made in parallel using different equipment or multipleoptical beam paths. For example, a second chamber can be filled withwater. Both the sample chamber and the second chamber (the referencechamber) can be probed at the same time.

Furthermore, not all three measurements I_(soil), I_(ref) and I_(dark)are always required. In some cases, similar or substitute informationmay be obtained from other sources. For example, if the spectrometer iswell characterized and stable, the dark count I_(dark) may be reliablysupplied by the manufacturer or determined by some other procedure. Asanother example, the attenuation spectrum may be estimated based on theintensity of the light before entering the sample chamber and theintensity of the light exiting the sample chamber. Alternately, thereference measurement may be based on a path where the light propagatesthrough air (or through an empty sample chamber) but not water. In somecases, it might be advantageous to have a simultaneous referencemeasurement of the beam (dual beam system), where the reference beamcould pass either through water (without soil) or through just air (nowater or soil). Factors such as the absorption of water may be accountedfor by models or methods other than direct measurement.

In one approach, the light can take two optical paths, one through thewater-soil mixture and another reference optical path not through thewater-soil mixture (e.g., through only air without water or soil). Thelight could be switched between the two paths, or it could be split intotwo beams, one for each path. The air-only reference measurementI_(refair) is compared to a reference measurement through water no soilI_(refwater). The relationship between the two is assumed to be fairlystable. In the field, the device makes measurements on the water-soilmixture I_(soil) and the air-only reference measurement I_(refair).I_(refwater) can then be determined from Lean based on the previouslydetermined relationship between I_(refair) and I_(refwater).

From the attenuation spectrum α(λ), the processor estimates thenitrate-nitrogen concentration. The concentration of nitrate-nitrogen(which has an absorption peak at 200 nm) could be estimated based solelyon comparing the attenuation spectrum at 200 nm against standards withknown nitrate-nitrogen concentrations. However, the measurement at 200nm is partly due to nitrate-nitrogen concentration and partly due toother interferences in the water-soil mixture. Thus, the estimate ofnitrate-nitrogen concentration can be significantly improved byaccounting for these other interferences.

Three common sources of interference to the UV nitrate-nitrogenmeasurement are scattering from soil particles, humic acids and/ororganic matter, and inorganic salts. FIG. 4A is a graph of anattenuation spectrum, identifying contributions from different sources.The curve 410 graphs the attenuation spectrum of an unfiltered,vigorously stirred 50:1 water:soil mixture, taken with a ˜1 mm pathlength cell. The soil has a nitrate concentration (measured via cadmiumreduction and a discrete analyzer) of ˜8.5 ppm. The spectrum shows aclear nitrate absorption peak near 200 nm, a weaker organic matterabsorption peak near 250 nm, and a broad background attenuation (˜1 at500 nm) due to scattering from soil particles.

FIG. 4B shows the attenuation spectra of two concentrated solutions ofdissolved salts, and illustrates how the spectral shape of the salts issignificantly different from that of nitrate-nitrogen. Curve 420 is for25 mMol KCl, and curve 430 is for 40 mMol (NH₄)₂SO₄. As a note, theconcentrations used in the graph are much higher than would be found ina typical soil. For example, typical soil levels of 0-1000 ppm K byweight would correspond to 0-20 ppm K in a 50:1 water:soil solution,while the inset shows K levels of ˜54,000 ppm by weight in solution. Itshould also be noted that taking a reference measurement of the waterwithout soil can be used to remove effects of interferences (ions,residual nitrate, etc.) from the water supply, thus eliminating the needfor distilled or purified water.

Different approaches can be used to account for these interferences.Some are based on physical models of the contributions from differentsources. Others are more empirical, for example training based on actualsamples with known nitrate-nitrogen concentrations.

At the preferred water:soil ratios of 20:1 or less, the scattering fromsoil particles is expected to present the largest background signal.However, the spectral shape of this background (which shows up as abroad absorption/extinction that steadily increases at shorterwavelengths) is different from the absorption of nitrate, which has awell-defined, Gaussian shape with a peak at 200 nm and a Gaussian widthof 20 nm. As a result of this spectral shape, spectral deconvolution andcurve-fitting techniques may be used to effectively remove thisinterference. Additionally, if needed, flocculents or salts could beadded to decrease the turbidity of the water soil mixtures, althoughthese materials should be chosen so as not to absorb in the UV region ofinterest.

Organic matter and humic acids are additional potential sources ofinterference due to their absorption in the UV. This is primarily due toconjugated carbon-carbon bonds which typically absorb around 254 nm,although this can vary depending on the particular molecular speciespresent. Appropriate curve-fitting algorithms may be used to remove theeffect of these spectrally distinct interferences. Additionally, soilorganic matter in agricultural soils is typically 1-10% as measured withthe loss-on-ignition technique, and only a small fraction of this isreactive (conjugated) carbon, so the magnitude of these interferences isexpected to be relatively small.

Some inorganic salts (such as KCl, NaCl, etc) can also absorb in thedeep UV when dissolved in solution. However, as with organic matter, thespectral shape of this absorption is typically quite different from theabsorption spectrum of nitrate-nitrogen, typically consisting of arelatively sharp increase in absorption with decreasing wavelength thatextends to below 190 nm. See the inset of FIG. 4, for example. Thisdistinct shape allows removal of this interference with appropriatecurve-fitting algorithms.

In one approach, the attenuation spectrum is modeled as consisting ofthe two nitrate-nitrogen absorption peaks (modeled as Gaussian curves at201 nm and 302 nm), and one or more Gaussian curves to account fornitrite, organic/humic matter absorption, and Rayleigh backgroundattenuation. By performing this type of analysis on a representative setof soils, the optimal fitting parameters to remove backgroundinterferences can be determined. An example of a possible fittingalgorithm is shown below

$\begin{matrix}{\mspace{79mu} {{{{Ab}\text{?}} \propto {\text{?} + {\sum\limits_{\;}^{\;}\; {C_{j}\text{?}}} + \left( {B_{R} - {A_{R}\log \; \lambda}} \right)}}{\text{?}\text{indicates text missing or illegible when filed}}}} & (2)\end{matrix}$

where λ is the wavelength, w_(j) is the width of the absorption peak forthe species of interest, λ_(j) is the center of the absorption peak, thesum over the C, terms are for potential absorption interferences (suchas nitrite, organic matter, etc.), and the A_(R) and B_(R) account forRayleigh scattering.

FIG. 5 illustrates curve fitting based on three Gaussians: one for thenitrate-nitrogen absorption peak at 200 nm (Gaussian 1), one forRayleigh scattering (Gaussian 2) and one for organic carbon (Gaussian3). The solid curve 510 shows the attenuation spectrum.

Other types of physical models can also be used. For example, it ispossible to remove the soil interferences from UV measurements on soilnitrate-nitrogen by fitting a broad background on top of the narrow (˜20nm full width) absorption peak at 200 nm due to nitrate-nitrogen.Particular embodiments of the background fitting functions could includea polynomial background, one or more Gaussian backgrounds or anempirically derived function. The narrow peak due to nitrate-nitrogencan be characterized by first measuring pure nitrate-nitrogen in theextractant and then using these measured absorption peaks and widths asfitting constants when performing the measurement on soil-extractantmixtures.

In a different approach, the estimate of nitrate-nitrogen concentrationcan be determined empirically, for example based on a learning algorithmor other adaptive or self-organizing algorithm. A training set includessamples of attenuation spectra and their corresponding nitrate-nitrogenconcentrations. The training set preferably covers the differentvariations expected in the field, for example different soil types andbackground contributions. This set is used to train the selectedalgorithm. A measured attenuation spectrum is then input to the trainedalgorithm, which estimates the nitrate-nitrogen concentration.

In one approach, partial least squares regression is used. Inpreliminary experiments, partial least squares regression was able toachieve +/−3.5 ppm accuracy. Note that an accuracy of 4 ppm for thenitrate-nitrogen concentration in soil corresponds to an accuracy of 0.2ppm for the nitrate-nitrogen concentration in a 1:20 soil:water mixture.This would be acceptable for many types of analysis. Other types ofprinciple components analysis can also be used.

Other sources of information can also be used. For example, if the soiltype is known (e.g., sandy, silty, clay), that can be used as an inputto estimate the nitrate-nitrogen concentration. Other factors such aspH, conductivity, soil:water mixture viscosity, soil moisture content,soil reflection spectrum, and soil density can also be used as inputs toestimate the nitrate-nitrogen concentration.

In some designs, in addition to estimating the nitrate-nitrogenconcentration, the processor also indicates the confidence in theestimate. For example, if it is difficult to fit a certain attenuationspectrum, the processor might provide an estimate but also flag thesample as a bad fit. This might occur, for example, if the attenuationspectrum included an unknown interference. If necessary, these samplescould then be discarded or sent to a lab for analysis.

FIG. 6 is a graph summarizing experiments. This experiment is based onten soil samples, representing a variety of soil types (sand, loam,clay, etc). Each dot represents one sample. For each of these samples,the nitrate-nitrogen concentration was estimated using the approachdescribed above (based on attenuation spectrum and the 200 nm absorptionpeak) and also using the standard Cd-reduction technique. The dashedline would be perfect correlation between the two techniques. The sampledots fall near the dashed line. These results indicate the viability ofquickly and accurately predicting soil nitrate-nitrogen levels atcommercially relevant levels using the technique described above.

In some cases, when mixing soil with an extractant, it can takesignificant time for the nutrient or nutrients of interest to dissolvein the extractant. FIG. 7 is a graph of nutrient concentration (e.g.,nitrate-nitrogen concentration) as a function of time, illustrating thetime extrapolation of final concentrations of the nutrient. This can beused to improve the measurement speed.

UV-visible spectroscopy equipment can give accurate signals aftermeasurement times much less than 1 second. The measurement of interestis often the final value after all of the relevant nutrients are part ofthe solution. The effective measurement time can be decreased by usingdata points, measured as a function of time, to predict the value atsaturation before the measured values become steady.

Referring to FIG. 7, the process begins with the mixing of soil andextractant. The concentration of the nutrient of interest (e.g.,nitrate-nitrogen concentration) is calculated at different times, thusyielding a plot of concentration vs time, as shown in FIG. 7. The datapoints are curve fit to a functional form that will predict the finalanswer (e.g., exponential or other asymptotic function). The curve fitis updated as more data points are collected. The error of the fit isalso estimated. The soil measuring cycle is terminated when theestimated error is less than some threshold value, or after some setmaximum measurement time has been exceeded. Referring to FIG. 7, incases where the measurement system is much faster than the underlyingextraction process, the fitting function can estimate the final valuewell before the extraction process actually reaches that value, thusreducing the time required to estimate concentration.

The process of fitting the data points can be done in a number ways. Oneapproach involves least squares regression of the data point to aphysically or chemically motivated formula for the time dependence. Onesuch function is a constant minus an exponentially decreasing function.Another function is a polynomial as a function of time. Another functionis some linear combination of these functional forms with variousfitting parameters. An alternate approach for fitting the timedependence is the use of a machine learning algorithm trained on a largeset of appropriately labeled data.

Parameters relating to the speed and shape of the time dependencefitting can also be provided. Examples of relevant parameters includemeasurements relating to the extractant/moisture content of the soil(correlating to the amount of nutrients that are already dissolved) andsoil composition (percentage clay, silt, sand, organic matter, etc.)which relates to the physical extraction processes.

In various embodiments, the attenuation spectrum can be obtained bytechniques other than propagating the light directly through thesoil-extractant mixture. For example, evanescent-field fiber absorptionspectroscopy or attenuated total reflection (ATR) are two alternatetechniques to measure the attenuation spectrum.

In other aspects, the estimates of nitrate-nitrogen concentration arecombined with other measurements. In one embodiment, an optical detectormeasures scattered light. This signal is used as an additional input toreduce the soil interferences, since small particulates (such as thosefound in a soil/extractant mixture) can strongly scatter light and thusinterfere with optical transmission measurements.

Another embodiment could contain optical reflectivity measurements ofthe soil before extractant mixing in the UV, visible, near IR, and/ormid IR spectra. The reflectivity of dry soil as a function of wavelengthis generally correlated to soil type. Such information can be used, inconjunction with the other embodiments discussed herein to provide dataof interest to the end user, and for additional tests.

Another embodiment includes the integration of additional measurementssuch as soil moisture, soil conductivity, temperature, ambient humidity,soil pH, soil/extractant solution viscosity, etc. which are useful intheir own right but can also be integrated with the above measurementsto increase accuracy. For example, by measuring the moisture content ofthe soil, the nitrate-nitrogen measurement can be made more accurate bysubtracting the weight of the water from the initial soil sample.

The approaches described above have many advantages. Certainimplementations have the potential to combine the accuracy of lab-basedsoil sampling but at a significantly faster speed and lower cost. Bymeasuring nitrate-nitrogen directly in the soil, the interferences thathinder indirect NDVI measurements are avoided. In addition, by using the200 nm absorption peak rather than the 300 nm absorption peak, lowerconcentrations of nitrate-nitrogen can be measured. To be agronomicallyrelevant, a nitrate-nitrogen measurement system generally should be ableto accurately measure soil nitrate-nitrogen concentration in the rangeof 0-50 ppm. Furthermore, the approach described above can beimplemented in a fast, portable instrument with no chemical reagents,thus offering a more timely and cost-effective high density analysiscompared to soil chemistry labs. Field instruments can be used toessentially sample nitrate-nitrogen concentration in real-time with highdensity across a field.

This can allow growers to rapidly and economically measure soilnitrate-nitrogen levels, thus enabling them to improve their fertilizermanagement decisions. For example, split application of nitrogen(through side-dressing) can greatly improve nitrogen use efficiency.However, side-dressing is time sensitive, and management decisions ofhow much nitrogen to apply are often limited by the cost and slowturnaround of current soil testing procedures. Fertilizer is asignificant agricultural cost and the inefficient use of fertilizer haslarge additional societal and environmental costs. Nitrous oxide arisingfrom nitrogen-based fertilizer use is a significant cause of the drivingforce for global warming, and nitrogen runoff from agriculture causesserious water quality issues. Thus, improving fertilizer management willhave large economic and environmental benefits.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs. Thus,while particular embodiments and applications have been illustrated anddescribed, it is to be understood that the present invention is notlimited to the precise construction and components disclosed herein andthat various modifications, changes and variations which will beapparent to those skilled in the art may be made in the arrangement,operation and details of the method and apparatus of the presentinvention disclosed herein without departing from the spirit and scopeof the invention as defined in the appended claims.

1. A device for measuring the nitrate-nitrogen concentration in soilbased on attenuation over a spectral operating range, the devicecomprising: a light source that generates light that spans the spectraloperating range, the spectral operating range including wavelengths atleast as short as 230 nm; a detector having a sensitivity that spans thespectral operating range; a sample chamber configured to contain asoil-extractant mixture; the light propagating from the light source tothe detector and attenuated by the soil-extractant mixture in the samplechamber, the detector generating a soil spectral signal that indicatesthe light received by the detector at different wavelengths across thespectral operating range; and a processor coupled to the detector,wherein the processor estimates an attenuation spectrum of thesoil-extractant mixture over the spectral operating range based on thesoil spectral signal, and estimates the nitrate-nitrogen concentrationbased on the attenuation spectrum.
 2. The device of claim 1 wherein thespectral operating range includes the 200 nm nitrate-nitrogen absorptionpeak.
 3. The device of claim 1 wherein the device is capable ofestimating nitrate-nitrogen concentrations below 50 ppm.
 4. The deviceof claim 1 wherein the sample chamber is optically positioned betweenthe light source and the detector, the light propagating through thesoil-extractant mixture in the sample chamber.
 5. The device of claim 1wherein the processor estimates the attenuation spectrum based on thesoil spectral signal, a reference spectral signal and a dark spectralsignal, wherein the reference spectral signal is generated when thesample chamber contains extractant without soil and the dark spectralsignal is generated without light from the light source incident on thedetector.
 6. The device of claim 1 wherein, at different times, thesample chamber contains the soil-extractant mixture or extractantwithout soil, the detector generating the soil spectral signal when thesample chamber contains the soil-extractant mixture and the detectorgenerating a reference spectral signal when the sample chamber containsextractant without soil, the processor estimating the attenuationspectrum based on the soil spectral signal and the reference spectralsignal.
 7. The device of claim 1 further comprising: a second samplechamber configured to contain extractant without soil, wherein theprocessor estimates the attenuation spectrum based on the soil spectralsignal and a reference spectral signal, wherein the reference spectralsignal is generated from the second sample chamber containing extractantwithout soil.
 8. The device of claim 1 further comprising: a referenceoptical path from the light source to the detector but not attenuated bythe soil-extractant mixture, wherein the processor estimates theattenuation spectrum based on the soil spectral signal and a referencespectral signal, wherein the reference spectral signal is generatedbased on the reference optical path.
 9. The device of claim 1 whereinthe spectral operating range includes a wavelength range from 190-500nm.
 10. The device of claim 1 wherein the spectral operating rangeincludes a wavelength range from 190-850 nm.
 11. The device of claim 1wherein the spectral operating range includes a wavelength range from180-1100 nm.
 12. The device of claim 1 wherein the spectral operatingrange includes a wavelength range of at least 20 nm full width centeredaround 200 nm.
 13. The device of claim 1 wherein the spectral operatingrange includes a wavelength range of at least 40 nm full width centeredaround 200 nm.
 14. The device of claim 1 wherein the spectral operatingrange includes a wavelength range of at least 60 nm full width centeredaround 200 nm.
 15. The device of claim 1 wherein the spectral operatingrange does not extend to wavelengths below 160 nm.
 16. The device ofclaim 1 wherein the spectral operating range extends to wavelengths atleast as short as 215 nm.
 17. The device of claim 1 wherein the spectraloperating range extends to wavelengths at least as short as 210 nm. 18.The device of claim 1 wherein the detected spectrum signal is sampled ata resolution of 1 nm or coarser.
 19. The device of claim 1 wherein thedetected spectrum signal is sampled at a resolution of 5 nm or coarser.20. The device of claim 1 wherein the detected spectrum signal issampled at a finer resolution around 200 nm than in the visible.
 21. Thedevice of claim 1 wherein the processor estimates the nitrate-nitrogenconcentration within 1 minute of the soil-extractant mixture enteringthe sample chamber.
 22. The device of claim 1 wherein the processorcurve fits the attenuation spectrum, at least one component of the curvefit based on the nitrate-nitrogen 200 nm absorption peak.
 23. The deviceof claim 1 wherein the processor receives a soil type and estimates thenitrate-nitrogen concentration further based on the soil type.
 24. Thedevice of claim 1 wherein the processor receives a soil conductivity andestimates the nitrate-nitrogen concentration further based on the soilconductivity.
 25. The device of claim 1 wherein the processor applies apartial least squares regression to the attenuation spectrum to estimatethe nitrate-nitrogen concentration.
 26. The device of claim 1 whereinthe processor is trained based on a set of absorption spectra and theircorresponding nitrate-nitrogen concentrations, and the processorestimates the nitrate-nitrogen concentration based on its training. 27.The device of claim 1 wherein the processor curve fits the attenuationspectrum, at least one component of the curve fit based on a Gaussianbackground spectrum.
 28. The device of claim 1 wherein the processorestimates the nitrate-nitrogen concentration as a function of time ofmeasurement and extrapolates the estimates to a final estimatednitrate-nitrogen concentration.
 29. The device of claim 1 wherein a pathof the light through the soil-extractant mixture is not more than 1 cmlong.
 30. The device of claim 29 wherein a path of the light through thesoil-extractant mixture is not more than 2 mm long.
 31. The device ofclaim 1 wherein a UV spectrum of the light source can be controlledseparately from a visible spectrum of the light source.
 32. The deviceof claim 31 wherein the light source includes two bulbs, one of whichhas a relatively stronger UV spectrum than the other, and which can beseparately controlled.
 33. The device of claim 1 further comprising: afilter that filters the soil-extractant mixture, the light propagatingthrough the filtered soil-extractant mixture.
 34. The device of claim 1wherein the light propagates through unfiltered soil-extractant mixture.35. The device of claim 1 further comprising: a centrifuge forseparating the soil-extractant mixture, the light propagating throughthe separated soil-extractant mixture.
 36. A method for measuring thenitrate-nitrogen concentration in soil based on attenuation over aspectral operating range, the method comprising: generating light thatspans the spectral operating range, the spectral operating rangeincluding wavelengths at least as short as 230 nm; providing asoil-extractant mixture that attenuates the light; detecting theattenuated light; generating a soil spectral signal that indicates thelight detected at different wavelengths across the spectral operatingrange; estimating an attenuation spectrum of the soil-extractant mixtureover the spectral operating range based on the soil spectral signal; andestimating the nitrate-nitrogen concentration based on the attenuationspectrum.